Intelligent Team and Topic Assignment

Intelligent assignment creates teams based off of each individual users ranking of topic preference, using k-means clustering. This webservice requires an input of each users ranks [1 being most preferred, and 0 indicating no preference] and unique id [pid], as well as the max team size. This also uses top trading cycles to switch members of teams who have already worked with other members on that team.

Accessing the service

Access the Webservice online

This service is hosted at: http://peerlogic.csc.ncsu.edu/intelligent_assignment/[method name]. This service can be called without copying the code onto your local machine, simply make a post request to this url with one of the method names mentioned below.

Run it on your local machine

The service can be copied from its github repository (https://github.com/peerlogic/IntelligentAssignment). It should be deployed as a webservice; though, it will also require the python libraries flask and scipy:

-[Scipy](https://www.scipy.org/scipylib/download.html)

-[Flask](https://pypi.python.org/pypi/Flask)

Methods

Creating teams (/merge_teams):

Uses K-means clustering to group users with similar topic interests. Works to eliminate competition for any single topic and increase the likelihood that each user obtains their most preferred topic.

Swapping Team Members (/swap_team_members):

Uses Top Trading Cycles to swap members, that have already worked with members on their team, with other teams’ members. This method only swaps a max of one member per team per run. Begins by first sorting the list of available members by distance from the teams centroid and then by whether or not other members of the team have worked with them. This method requires a history of users that each user has worked with, along with the general information.